from fastai.vision.all import *
from io import BytesIO
import requests
import streamlit as st

"""
# U-Net
This is a segmentation model for images of Brain MRI.
"""

def predict(img):
    st.image(img, caption="Your image", use_column_width=True)
    pred_mask = learn_inf.predict(img)[0]
    pred_mask = pred_mask.numpy()*255
    # pred, key, probs = learn_inf.predict(img)
    # st.write(learn_inf.predict(img))

    f"""
    ### Rediction result:
    """
    st.image(pred_mask, caption="Prediction Mask", use_column_width=True)

def label_func(x):
    return x.parents[0] / (x.stem + '_mask' + x.suffix)
      
path = "./"
learn_inf = load_learner(path + "model-34")

option = st.radio("", ["Upload Image", "Image URL"])

if option == "Upload Image":
    uploaded_file = st.file_uploader("Please upload an image.")

    if uploaded_file is not None:
        img = PILImage.create(uploaded_file)
        predict(img)

else:
    url = st.text_input("Please input a url.")

    if url != "":
        try:
            response = requests.get(url)
            pil_img = PILImage.create(BytesIO(response.content))
            predict(pil_img)

        except:
            st.text("Problem reading image from", url)